MicroRNA Dysregulation in Early Breast Cancer Diagnosis: A Systematic Review and Meta-Analysis

Breast cancer continues to be the leading cause of death in women worldwide. Mammography, which is the current gold standard technique used to diagnose it, presents strong limitations in early ages where breast cancer is much more aggressive and fatal. MiRNAs present in numerous body fluids might represent a new line of research in breast cancer biomarkers, especially oncomiRNAs, known to play an important role in the suppression and development of neoplasms. The aim of this systematic review and meta-analysis was to evaluate dysregulated miRNA biomarkers and their diagnostic accuracy in breast cancer. Two independent researchers reviewed the included studies according to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. A protocol for this review was registered in PROSPERO with the registration number “CRD42021256338”. Observational case-control-based studies analyzing concentrations of microRNAs which have been published within the last 10 years were selected, and the concentrations of miRNAs in women with breast cancer and healthy controls were analyzed. Random-effects meta-analyses of miR-155 were performed on the studies which provided enough data to calculate diagnostic odds ratios. We determined that 34 microRNAs were substantially dysregulated and could be considered biomarkers of breast cancer. Individually, miR-155 provided better diagnostic results than mammography on average. However, when several miRNAs are used to screen, forming a panel, sensitivity and specificity rates improve, and they can be associated with classic biomarkers such us CA-125 or CEA. Based on the results of our meta-analysis, miR-155 might be a promising diagnostic biomarker for this patient population.


Introduction
The incidence of breast cancer follows a growing pattern, especially in recent decades. Based on data from the GLOBOCAN 2020 study, this neoplasm exceeded the incidence of lung cancer, establishing it as the most prevalent neoplasm worldwide [1]. Regarding mortality, breast cancer constitutes the second oncological cause of death in women. Accordingly, it is estimated that one in four women will suffer from breast cancer throughout her life and one in six will die from this ailment.
Early diagnosis notably improves the long-term survivability rates of breast cancer [2]. The most widely used diagnostic techniques for breast cancer screening consist of imaging techniques. Among them, mammography is considered the gold standard technique in breast cancer screening. Similarly, ultrasounds have shown great efficacy as a complementary technique to detect potential false-negative cases [3]. Other advanced imaging techniques, such as magnetic resonance imaging (MRI) or positron emission tomography (PET), have notable specificity and sensitivity values, enabling the identification of lesions

Materials and Methods
To achieve the proposed objectives, we conducted a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. We conducted a qualitative analysis to screen microRNAs with diagnostic potential. Subsequently, a quantitative data synthesis was conducted to evaluate the diagnostic accuracy of specific miRNAs. This review was registered in the International Prospective Register of Systematic Reviews (PROSPERO) with the registration number "CRD42021256338".

Search Strategy
A thorough search of relevant articles from the PubMed (Medline), Scopus, and CINAHL databases was performed by one reviewer. Considering that miRNA concentrations in individuals with and without breast cancer have been extensively reported in previous decades, the studies were limited only to those published between 2010 and 2021, using different combinations of the following search terms: "microRNA", "miRNA", "miR", "breast cancer", "breast neoplasm", "early diagnosis", and "screening". The searches were limited to articles published in English. Keywords were selected using the Medical Subject Heading (MeSH) terms based on the patients, interventions, comparators, results, and study design defined for the present study (PICO). The results obtained through the different search queries were combined using the Mendeley software (v. 1.19.8), eliminating duplicated articles. Two reviewers screened the titles and abstracts of studies identified in the initial search to determine the relevance of these publications. Then, full texts were obtained and reviewed in detail. Finally, 38 articles were included in this systematic review after the screening and selection processes.

Study Selection
Articles were considered eligible if they met all of the following inclusion and exclusion criteria: The inclusion criteria consisted of: (1) studies conducted on pregnant women, including cases of breast cancer diagnosed by a validated method; (2) case-control studies; (3) studies assessing the expression of breast cancer-related miRNAs; (4) sample sizes ≥ 20.
The exclusion criteria included: (1) studies conducted on animal models; (2) studies with very high risk of bias, evaluated using the NOS scale (Newcastle-Ottawa Scale for Observational Studies), which is detailed in Supplementary Table S1; (3) studies that use an miRNA for normalization with poor scientific evidence of its variation in cases versus controls; (4) studies including women with other diagnosed pathologies that might bias results (i.e., another type of cancer).
The meta-analysis inclusion criteria were as follows: (1) miRNAs evaluated in least three different studies.; (2) articles reporting sufficient raw data to construct a 2 × 2 contingency table of true positives (TP), true negatives (TN), false positives (FP), and false negatives (FN), or providing sensitivity and specificity values.
The exclusion criteria included only one item: low quality assessed by the QUADAS-2 tool.

Quality Assessment
Two independent reviewers assessed the risk of bias in the selected studies using the Newcastle-Ottawa scale for observational studies of case-control design. Studies with a score of 0-3 stars were considered to present a very high risk of bias and were thus excluded from this review. Studies with a score of 4-6 were considered to present a high risk of bias, and studies that achieved a score of ≥7 were considered to be of a high quality/present a low risk of bias.
To ensure the quality of the meta-analysis, the six studies included were evaluated by following the second version of the Quality Assessment of Diagnostic Accuracy Test (QUADAS-2), which evaluates four key domains: patient selection, index test, reference standard, and flow and timing. Studies with a score of less than 7 were considered to have a high risk of bias and low applicability and were thus excluded from this metaanalysis. Disagreements regarding individual studies were discussed and resolved to reach a consensus between the reviewers.

Data Extraction
A template was created with the following data: author, year, age, normalization method, sample size of all groups, miRNA(s) profiled, and sample source. The extracted data were managed using the software Microsoft Excel ® . Data were extracted independently by two reviewers. Whenever disagreements between the reviewers occurred, a third reviewer was the arbiter.

Statistical Analysis
For diagnostic accuracy, the included studies' sensitivity, specificity, diagnostic odds ratio (DOR), positive and negative likelihood ratios (PLR and NLR), and corresponding 95% CI were pooled to assess the diagnostic value of miRNA-155 in breast cancer. The summary receiver operating characteristic (SROC) curve was plotted based on the original data, and the area under the SROC curve (AUC) was calculated to determine the diagnostic accuracy of miR-155. The I 2 and Chi tests were conducted to estimate the proportion of total variation among studies that occurred due to heterogeneity rather than chance. I 2 values of >50% were considered to be indicative of significant heterogeneity among the included studies, and thus a random effects model was applied in the analyses [13]. Quantitative analysis of publication bias was assessed using the Deek's test and creating funnel plots. Subsequently, meta-regression analyses were carried out to find the potential sources of heterogeneity. Finally, the risk of publication bias of all the included studies was estimated by Deeks' funnel plots [14]. All statistical analyses were performed using RevMan and Stata version 12 (Stata Corporation, College Station, TX, USA).

Characteristics of the Included Studies
The screening process of the eligible studies is presented in Figure 1. To study the diagnostic value of miRNAs, a total of thirty-eight articles were finally included for qualitative synthesis. Out of the total selected original studies, thirty examined miRNAs' expression levels between confirmed cases and healthy controls. The remaining eight studies compared the expression of selected miRNAs between a cancerous tissue versus an adjacent healthy tissue. The data extracted from the included papers are presented in Table 1. In Table 2, data on specific miRNAs were drawn and pooled from the included studies according to the combined sample of all those studies in which they were analyzed, including total cases and controls, how they were found to be dysregulated, the biological sample in which they were measured, and their relative value as reported by the authors. 95% CI were pooled to assess the diagnostic value of miRNA-155 in breast cancer. The summary receiver operating characteristic (SROC) curve was plotted based on the original data, and the area under the SROC curve (AUC) was calculated to determine the diagnostic accuracy of miR-155. The I 2 and Chi tests were conducted to estimate the proportion of total variation among studies that occurred due to heterogeneity rather than chance. I 2 values of > 50% were considered to be indicative of significant heterogeneity among the included studies, and thus a random effects model was applied in the analyses [13]. Quantitative analysis of publication bias was assessed using the Deek's test and creating funnel plots. Subsequently, meta-regression analyses were carried out to find the potential sources of heterogeneity. Finally, the risk of publication bias of all the included studies was estimated by Deeks' funnel plots [14]. All statistical analyses were performed using RevMan and Stata version 12 (Stata Corporation, College Station, TX, USA).

Characteristics of the Included Studies
The screening process of the eligible studies is presented in Figure 1. To study the diagnostic value of miRNAs, a total of thirty-eight articles were finally included for qualitative synthesis. Out of the total selected original studies, thirty examined miRNAs' expression levels between confirmed cases and healthy controls. The remaining eight studies compared the expression of selected miRNAs between a cancerous tissue versus an adjacent healthy tissue. The data extracted from the included papers are presented in Table 1. In Table 2, data on specific miRNAs were drawn and pooled from the included studies according to the combined sample of all those studies in which they were analyzed, including total cases and controls, how they were found to be dysregulated, the biological sample in which they were measured, and their relative value as reported by the authors.   The expression of miR-155 was significantly higher in the cases group. After receiving treatment (surgery and chemotherapy), the expression decreased significantly. miR-155 overexpression was also related to tumor size and stage. The expression of miR-1204 was significantly higher both in the tissue and in the serum of the cases compared to the controls, allowing the cases to be discriminated from the controls with a ROC curve of 0.854. miR-34a miR-10b [23] miR-16 Serum 118 89 29 The microRNAs analyzed were significantly elevated in the cases. miR-10b and miR-34a were significantly higher in patients with metastases compared to patients with localized breast cancer. Elevation of miR-34a correlated with advanced stages. The concentrations of all miRNAs were significantly higher in cases. The ROC curve showed that three of them (miR-145, miR-155, and miR-382) are potential biomarkers. Possible differences in the expression of the cases were also analyzed, although they were not significant (different stages) miR-21 miR-106a miR-126 miR-155 miR-199a miR-335 [25] miR-16 Serum 108 68 40 The concentrations of the microRNAs were significantly different between the cases and the controls. miR-21, miR-106a, and miR-155 were overexpressed and miR-126, miR-199a, and miR-335 were underexpressed. miR-21 and miR-451 were found to be significantly overexpressed in the cases, while miR-145 was underexpressed with respect to the controls. The combination of miR-145 and miR-451 presented a ROC curve of 96%, with an optimal sensitivity of 90% and specificity of 96%. These markers are not elevated for other types of cancer and are useful in different stages of breast cancer, with higher diagnostic values in some types of breast neoplasms, such as DCI (ductal carcinoma in situ), which obtained a ROC curve of 98% miR-21 miR-146a [27] miR-16 Serum 22 14 8 The expression of miR-21 and miR-146a were found to be significantly higher in the cases compared to the controls.
miR-21 miR-92a [28] RNU6 Serum 120 100 20 Significant overexpression of miR-21 and significant underexpression of miR-92a. Subsequent analysis showed that low miR-92a and high miR-21 levels were associated with tumor size and lymph node staging. [29] miR-54 Serum and tissue 32 16 16 Several microRNAs were encapsulated or highly enriched and selectively secreted by tumor exosomes. Both miR-21 and miR-1246 showed significantly high expression in the cases. miR-122 and let-7a are also considered to be potential biomarkers as they are selectively secreted. Only miR-195 was found to be significantly overexpressed in patients with breast cancer specifically, compared to cases of other neoplasms and healthy controls. Furthermore, a positive correlation between miR-195 levels and tumour size was demonstrated.

miR-21 miR-1246
On the other hand, let-7a was significantly elevated in the cases (with the exception of malignant melanoma). In patients with breast neoplasms, the simultaneous use of three miRNAs (let-7a, miR-195, and miR-155) led to a sensitivity of 94%.
In invasive breast cancer, the underexpression of miR-145 and overexpression of miR-210 were observed. In metastatic breast cancer, the underexpression of miR-205 and overexpression of miR-361-5p were observed.
miR-133a miR-155 p53 CEA CA-15.3 [33] SNORD68 Serum 80 60 20 While miR-155 was significantly overexpressed in the cases, miR-133a was significantly underexpressed. Both CEA and CA-15.3 were found to be significantly elevated in the serum of the cases. A possible relationship was found between miR-133a and tumour stage (underexpression-higher stage) and between miR-155 and lymph node metastasis (overexpression-lymph nodes involved).

miR-21
MMP-1 [34] miR-16 Urine 48 22 26 miR-21 was found to be significantly underexpressed in the cases, in contrast to the matrix metalloproteiase-1 (MMP-1), which was found to be significantly overexpressed. Combined, sensitivity reached 95% and specificity was 79%.  [39] miR-16 Serum 83 55 28 The cases were shown to have a higher expression of miRNAs. The expression of miR-34a was significantly lower in the cases, unlike CEA and CA 15-3. The combination of CEA or CA 15-3 together with miR-34a yielded ROC curves of 0.844 and 0.800, respectively. The specificity of the combination of miR-34a and CA 15-3 was 95%.
When the cohort of patients with breast cancer was compared with benign diseases, both sensitivity and specificity and the ROC curve showed better results. The expressions of miR-23a-3p, -130a-5p, -144-3p, -148a-3p, and 152-3p were lower in the plasma of the cases compared to the controls. miR-130a-5p, -144-3p, and 152-3p were also found to be underexpressed in the tissue of the cases.
The expression of miR-23a-3p, -144-3p, and 152-3p was related to ER and PR + status, in addition to showing significant differences in stage, especially in the early stages.

Data Normalization
In most studies, some form of normalization of circulating miRNA levels was reported to help compensate for potential variations between biological species. miR-16 was used as endogenous control in most of the studies (40%) [15,16,20,21,23,25,27,30,31,34,37,39,42], following by miR-39 and RNU38B. Articles that used an endogenous control that had been reported to be poorly detectable and highly variable were excluded.

Quality of Included Studies
The evaluation of the methodological quality of the studies analyzed in this review is shown in the Supplementary Information. Thirty-four studies had results that ranged from seven to nine stars (high quality studies), and four articles had between five and six stars. All of the studies selected cases according to valid diagnostic tests (i.e., biopsy) or independent validation, excluding cases for whom breast cancer was not primary. The controls belonged to the same community (generally the same hospital from which the cases were recruited) and had no history of disease.
All of the studies included scored more than seven out of ten. As a result, significant bias was not presented in the meta-analyses, as suggested in Figure 2, which represents detailed information regarding QUADAS-2 assessment. One article was excluded for high risk of bias, and four were excluded for missing information (see Figure 2 for detailed QUADAS-2 score).

Data Normalization
In most studies, some form of normalization of circulating miRNA levels was reported to help compensate for potential variations between biological species. miR-16 was used as endogenous control in most of the studies (40%) [15,16,20,21,23,25,27,30,31,34,37,39,42], following by miR-39 and RNU38B. Articles that used an endogenous control that had been reported to be poorly detectable and highly variable were excluded.

Quality of Included Studies
The evaluation of the methodological quality of the studies analyzed in this review is shown in the Supplementary Information. Thirty-four studies had results that ranged from seven to nine stars (high quality studies), and four articles had between five and six stars. All of the studies selected cases according to valid diagnostic tests (i.e., biopsy) or independent validation, excluding cases for whom breast cancer was not primary. The controls belonged to the same community (generally the same hospital from which the cases were recruited) and had no history of disease.
All of the studies included scored more than seven out of ten. As a result, significant bias was not presented in the meta-analyses, as suggested in Figure 2, which represents detailed information regarding QUADAS-2 assessment. One article was excluded for high risk of bias, and four were excluded for missing information (see Figure 2 for detailed QUADAS-2 score).

Diagnosis Test Accuracy Meta-Analysis
Six articles fit the inclusion and exclusion criteria to be part of this meta-analysis. Figure 3 indicates the individual characteristic of the articles included.

Diagnosis Test Accuracy Meta-Analysis
Six articles fit the inclusion and exclusion criteria to be part of this meta-analysis. Figure 3 indicates the individual characteristic of the articles included. Figure 3. Summary of studies [18,19,24,37,47,49] included in miR-155 meta-analysis.

Diagnosis Test Accuracy Meta-Analysis
Six articles fit the inclusion and exclusion criteria to be part of this meta-analysis. Figure 3 indicates the individual characteristic of the articles included. Figure 3. Summary of studies [18,19,24,37,47,49] included in miR-155 meta-analysis.

Subgroup Analysis
A subgroup analysis of the sample (serum) analyzed was performed to investigate the potential origin of heterogeneity between studies. The pooled results of this subgroup analysis are shown in Figure 8. It can be observed that studies that analyzed microRNA-155 in serum showed a slight improvement in diagnosis accuracy: the pooled sensitivity and specificity were 88% (95% CI: 69-96%) and 94% (95% CI: 78-99%), respectively. The PLR and NLR were 15.

Publication Bias
To distinguish the potential publication bias across the enrolled diagnostic studies, the Deeks funnel-plot test was performed. The Deeks' funnel plot (Figure 9) was symmetrical and reached a p value of 0.31 above 0.05, indicating there is no obvious publication bias in the included studies.

Publication Bias
To distinguish the potential publication bias across the enrolled diagnostic studies, the Deeks´ funnel-plot test was performed. The Deeks' funnel plot (Figure 9) was symmetrical and reached a p value of 0.31 above 0.05, indicating there is no obvious publication bias in the included studies.

Discussion
Breast cancer is the worldwide leading cancer in terms of diagnoses, with a tota 2.3 million new cases (11.7%) of breast cancer occurring yearly [1] Its mortality constit 6.9% of all deaths due to cancer. According to the SEER database, an authoritative so for cancer statistics in the United States, mortality from this neoplasm triples after the of 55, from 8.3% in the 35-44 age group to 25.6% in the 55-74 age range. If breast canc detected when it is confined to the primary site or has disseminated to regional lym nodes, the five-year relative survival is 93% [52]. Imaging technology has improved diagnosis of breast cancer patients and the development of surgical techniques, while current radiotherapy and chemotherapy have significantly reduced mortality compa to previous decades [53]. An ideal biomarker should have the ability to detect with h accuracy the onset of the disease even before any clinical signs appear. In additio should accurately discriminate between a neoplastic sample and a healthy sample, rep ing variations when the neoplasm is treated or during relapses. Moreover, idea omarkers should have a long half-life in clinical samples and should be accessible thro innocuous methods, stable, and serially reproducible with low cost [54]. MicroRNAs provide a solution to the existing problems with current screening techniques in the e diagnosis of breast cancer. They are truly stable biomolecules, present in body fluids s as serum, plasma, or saliva. Their expression is specific and sensitive in both tissues organs affected by a neoplasm [17,22,29,55], and their quantification method, by qRT-P or microarray [56], is simple and relatively inexpensive due to the worldwide adapta that has been made to enable the extensive use of this technique for the detection of SARS-CoV-2 viral genome. MiRNAs control the expression of target genes by eithe hibiting protein translation or directly targeting the mRNA transcripts of target gene degradation [12], with well-described roles in several cancers, including breast cancer Since miRNAs potentially have a broad influence on diverse genetic pathways, dysre lation of these small RNAs is probable to contribute to the occurrence of diseases, inc ing cancer.  [18,19,24,37,47,49].

Discussion
Breast cancer is the worldwide leading cancer in terms of diagnoses, with a total of 2.3 million new cases (11.7%) of breast cancer occurring yearly [1] Its mortality constitutes 6.9% of all deaths due to cancer. According to the SEER database, an authoritative source for cancer statistics in the United States, mortality from this neoplasm triples after the age of 55, from 8.3% in the 35-44 age group to 25.6% in the 55-74 age range. If breast cancer is detected when it is confined to the primary site or has disseminated to regional lymph nodes, the five-year relative survival is 93% [52]. Imaging technology has improved the diagnosis of breast cancer patients and the development of surgical techniques, while concurrent radiotherapy and chemotherapy have significantly reduced mortality compared to previous decades [53]. An ideal biomarker should have the ability to detect with high accuracy the onset of the disease even before any clinical signs appear. In addition, it should accurately discriminate between a neoplastic sample and a healthy sample, reporting variations when the neoplasm is treated or during relapses. Moreover, ideal biomarkers should have a long half-life in clinical samples and should be accessible through innocuous methods, stable, and serially reproducible with low cost [54]. MicroRNAs may provide a solution to the existing problems with current screening techniques in the early diagnosis of breast cancer. They are truly stable biomolecules, present in body fluids such as serum, plasma, or saliva. Their expression is specific and sensitive in both tissues and organs affected by a neoplasm [17,22,29,55], and their quantification method, by qRT-PCR or microarray [56], is simple and relatively inexpensive due to the worldwide adaptation that has been made to enable the extensive use of this technique for the detection of the SARS-CoV-2 viral genome. MiRNAs control the expression of target genes by either inhibiting protein translation or directly targeting the mRNA transcripts of target genes for degradation [12], with welldescribed roles in several cancers, including breast cancer [56]. Since miRNAs potentially have a broad influence on diverse genetic pathways, dysregulation of these small RNAs is probable to contribute to the occurrence of diseases, including cancer.

Size and Angiogenesis
MicroRNAs have been significantly linked to tumor development and angiogenesis. There is a balance between proangiogenic and antiangiogenic factors that work together with different expressions, releasing or reactivating factors with the ability to form new blood vessels [57]. The process of angiogenesis in normal cells is different from the angiogenic process that develops in tumor cells. Tumor blood vessels are highly disorganized, irregular in shape, and hyperpermeable, among other characteristics [58]. Tightly linked to this event is tumor size; as the tumor increases in size, aerobic conditions begin to be compromised and tissue hypoxia occurs. This hypoxia promotes the release of angiogenic factors and angiovascular mimicry, also known as EMT (endothelial-mesothelial transition). This change allows the tumor cell to restructure its phenotypic expression and show itself as an endothelial cell, and this will have very important repercussions related to its invasiveness [59].
The underexpression of miRNAs related to angiogenesis inhibition and the overexpression of those related to angiogenesis promotion described in the studies included in our work support their diagnostic utility, as they are related to tumor growth, invasion, and metastasis.

Angiogenesis and Tumor Spreading
Neovascularization, described hereinbefore, provides a direct gateway to other organs and tissues that are colonized by tumor cells, causing tumor dissemination. When a tumor cell acquires the ability to migrate to other tissues distant from the primary cancer, usually through lymphatic or blood vessels, it can begin to reproduce and invade new organs, spreading to various areas of the body [67,68].
MicroRNAs can control invasion and metastasis processes in many ways [69], such as the cell secretion of factors such as TGF-β, involved in cell growth and the proliferation of tumor cells in early stages and contributing to EMT [70]; or through interaction with the Wnt/β-cateninn pathway, which inhibits the expression of a protein attached to the cell membrane (E-cadherin), whose loss is associated with EMT [71]. Among the microRNAs that promote these processes are miR-21 (through TGF-β and epidermal growth factor) [72], miR-10b (TGF-β1, its expression enhances E-cadherin expression) [73], miR-155 (RhoA) [74], and miR-191 (TGF-β1) [75]. Among the microRNAs that prevent metastasis are miRNA-141 and miRNA-200c [76]. In our revision, miRNAs that promote metastasis were found to be significantly overexpressed, while those that suppress it were found to be downregulated. The detection of the overexpression of miRNAs involved in angiogenesis or those that are suppressed or underexpressed for the same reason in combination with tumor markers (e.g., TGF-β, VEGF, CEA or CA15-3) could anticipate a diagnosis before tumor dissemination is produced, helping the treatment response and a reduction in sequels.
Several reports have shown that miR-155 acts as an oncomiR in human cancers by targeting tumor suppressors [77,78]. It has been revealed that miR-155 promotes cancer cell proliferation (EMT), CSC phenotype [79], chemoresistance [80,81], the evasion of apoptosis, colony formation, and tumor growth. In our meta-analysis, the AUC and corresponding 95% CI were 0.96 (0.94-97). In addition, PLR and NLR were 15.90 (95% CI: 3.35-75.46) and 0.13 (95% CI: 0.04-0.37), respectively, in serum, indicating that microRNA-155 could discriminate breast cancer patients from healthy patients with relative reliability. Traditional markers such as CEA or CA 15-3 can also benefit from microRNAs. The main disadvantage of these traditional markers is their low sensitivity, which is improved when used in combination with microRNAs, as reported by Zaleski [39] A further highlight of our work is the diagnostic value of this microRNA in different fluids. In Erbes's research [49], miR-155 was measured in urine, and despite being underexpressed in this fluid as opposed to serum, where it is overexpressed, its sensitivity and specificity were very similar, as disclosed in our subgroup analysis, which may guide future research on other fluids with closer contact with the tumor environment, such as breast milk.
Last but not least, ethnic and racial representation is limited in the area of early detection of breast cancer using microRNAs. Studies have included only Caucasian and Asian patients. The fact that race and ethnicity correlate with breast cancer morbidity and mortality has been documented by some authors [82][83][84][85]. Generally, these characteristics are associated with socioeconomic disparities, as, in the case of black patients, several studies suggest a higher mortality and a significantly lower overall five-year survival [86][87][88]. Another fact that explains the higher mortality in ethnic minorities is the higher incidence and outcome disparities of very aggressive breast cancers, such as triple-negative breast cancer [89,90].

Heterogeneity: A Major Challenge to Overcome
Finally, when evaluating the results presented, some limitations must be taken into account: (1) a common feature of all of the studies reviewed both in our systematic review and in the subsequent quantitative analysis was the high biological and technical variability, which was a major source of bias. The sample preparation (the use of small, enriched RNA fraction versus total miRNA), methods used to isolate RNA (phenol/guanidinium (TRIzol, Invitrogen), miRNeasy (QIAGEN), and mirVana (ABI) . . . ), and the differences in the selection of endogenous controls (miR-16, -39, 222-3p, among others) encourage inconsistency in the results obtained. Regarding endogenous controls, miR-16 is recognized by several authors as the most stably expressed microRNA in breast cancer patients and healthy controls [91][92][93]. (2) Racial factors were not represented in their scope. The included articles presented a monotonous Caucasian and Asian population. The African race should be studied more widely, especially because of the greater incidence of breast cancer in this community. Therefore, more researchers should pay attention to the impact of racial factors in subsequent studies. (3) Our work only included articles published in English, but did not cover articles in other languages. (4) The sample size was too small, which may undermine the reliability of our results. Therefore, more well-designed studies based on larger samples and sufficient data are required to verify the diagnostic value of miR-155. (5) Subgroup analysis could not be performed in our meta-analysis because of the limited data for adjustment for covariates such as TNM stage, histologic type, assay, and so on [94].

Conclusions
In summary, the results reported in the present study may be useful for future confirmatory analyses more focused on the expression of preselected miRNAs in breast cancer patients. The miRNAs constitute a new avenue to explore to complement the use of classical breast cancer biomarkers, thereby improving sensitivity and specificity, and to be used as an isolated approach, particularly when these are pooled to form panels. Based on the results of our meta-analysis, miR-155 might be a promising diagnostic biomarker for this patient population. It is a blood-based biomarker that is easy to obtain and non-invasive. At the same time, this biomarker is highly stable. In the same way that certain miRNA expression profiles in blood appear to be specific-such as miR-122, expressed preferentially in liver and miR-133, expressed in muscle-miR-155 could be breast-specific. Moreover, it is noteworthy that different laboratories studying the same disease find the same circulating miRNAs as potential biomarkers, which strengthens the idea that miRNAs may be valid for diagnosing cancer and other diseases. Nevertheless, large-scale, well-designed, multicenter studies should be conducted to clarify the mechanism of miR-155 overexpression in breast cancer.